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image/svg+xml
    [4]:
    display(dados_RH)
    COD_FUNC NOME SALARIO DATA_NASCIMENTO SEXO ENDEREÇO COD_CARGO Unnamed: 7 Unnamed: 8 Unnamed: 9 Unnamed: 10
    0 1.0 Carlos Dias 9642.31 21/12/1985 Masculino Rua das Flores, 896, Arujá 1.0 NaN NaN NaN NaN
    1 2.0 Maria Clara 1500.00 13/09/1992 Feminino Rua Gardenia, 3600, São Paulo 4.0 NaN NaN NaN NaN
    2 3.0 Antunes Silveira 3520.00 21/04/1983 Masculino Rua das Rosas, 568, Arujá 2.0 NaN NaN NaN NaN
    3 4.0 Silvio Prado 3120.00 12/08/1997 Masculino Rua Hermenegildo, 102, Guarulhos 4.0 NaN NaN NaN NaN
    4 5.0 André Souza 4800.00 06/08/2002 Masculino Rua Serra, 56, Guarulhos 2.0 NaN NaN NaN NaN
    5 6.0 José Antonio 2500.00 25/11/1996 Masculino Rua Neto Brito, 89, São Paulo 1.0 NaN NaN NaN NaN
    6 7.0 Dias Davila 6500.00 02/02/1994 Masculino Rua das Elenice, 78, Guarulhos 5.0 NaN NaN NaN NaN
    7 8.0 André Souza 1850.00 23/06/1988 Masculino Rua das Flores, 1800, São Paulo 4.0 NaN NaN NaN NaN
    8 9.0 Marcos Andrade 3500.00 28/07/1989 Masculino Rua Grande Sul, 40, São Paulo 3.0 NaN NaN NaN NaN
    9 10.0 Paula Santos 4200.00 12/06/1998 Feminino Avenida José Teodoro, 40, Arujá 2.0 NaN NaN NaN NaN
    10 11.0 Gabriel Oliveira 100.00 18/03/2007 Masculino Rua Jose Viera De Lima, 69, Guarulhos 6.0 NaN NaN NaN NaN
    11 NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN
    12 NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN
    13 NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN
    14 NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN
    15 NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN
    16 NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN
    17 NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN
    18 NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN
    19 NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN
    20 NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN
    21 NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN
    22 NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN
    23 NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN
    24 NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN
    25 NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN
    26 NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN
    27 NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN
    28 NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN
    29 NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN
    30 NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN
    31 NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN
    32 NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN
    33 NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN
    34 NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN
    35 NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN
    36 NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN 0.0
    [5]:
    fig = grafico.line (dados_RH, x='NOME',y='SALARIO', title = 'Relação Funcionário x Salario')
    fig.show()
    Carlos DiasMaria ClaraAntunes SilveiraSilvio PradoAndré SouzaJosé AntonioDias DavilaMarcos AndradePaula SantosGabriel Oliveira02k4k6k8k10k
    Relação Funcionário x SalarioNOMESALARIO
    plotly-logomark
    [6]:
    fig = grafico.bar (dados_RH,x='SEXO',y='SALARIO', title='Relação Salário x Sexo')
    fig.show()
    MasculinoFeminino010k20k30k
    Relação Salário x SexoSEXOSALARIO
    plotly-logomark
    [ ]:

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